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get_nearby_crashes

Find Colorado crash records near an attorney's office by supplying an attorney slug. Adjust radius, date range, and result limits to identify relevant cases.

Instructions

Get crash records near a specific attorney's office location. This tool is attorney-centered, not a raw lat/lng search. Use a canonical attorney slug from search_attorneys, then this tool will search around that office address.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoSort by distance or datedistance
limitNoMax results (1-200, default 50)
monthsNoLook-back period in months (1-120, default 12)
radius_kmNoSearch radius in km (0.5-50, default 3)
attorney_slugYesCanonical attorney slug from search_attorneys, used as the center point
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full transparency burden. It implies a read operation ('Get') and notes the search is centered on the attorney's office address, which is useful. However, it does not disclose potential caveats like approximate address matching, rate limits, or whether results are paginated. This is a moderate gap, but the core behavior is clear enough for a basic understanding.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences long, front-loading the primary purpose and then adding necessary usage context. Every sentence is informative, with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema, so the description should ideally explain what the response contains. It mentions 'crash records' but does not clarify the structure (e.g., whether distances are included) or how records relate to the office location. Given the well-documented parameters and clear purpose, this is adequate but leaves some ambiguity for an agent preparing to use the results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, providing a baseline of 3. The description adds extra meaning to the required parameter attorney_slug by specifying it must be a canonical slug from search_attorneys and serves as the center point, while also clarifying that the tool is not raw lat/lng search. This adds value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Get crash records near a specific attorney's office location') and clearly differentiates this tool from a raw lat/lng search by emphasizing it is attorney-centered. This distinguishes it from sibling tools like search_crashes, which presumably perform generic searches.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells the user to first obtain a canonical attorney slug from search_attorneys, and clarifies this tool is not for raw coordinate searches. This provides clear when-to-use and prerequisite guidance, effectively steering users away from misuse.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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